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Related Concept Videos

Archival Research01:40

Archival Research

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Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research. Archival research relies on looking at past records or data sets to look for interesting patterns or relationships. For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and...
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Longitudinal Research02:20

Longitudinal Research

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Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
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RACE - Rapid Amplification of cDNA Ends02:35

RACE - Rapid Amplification of cDNA Ends

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Rapid Amplification of cDNA Ends, or RACE, is one of the most effective methods to obtain a full-length cDNA from an mRNA sequence between a known internal region to the unknown sequence at the 5’ or 3’ end. The unknown region is cloned in the cDNA by a gene-specific primer that binds the known end, and a hybrid primer that attaches a predefined anchor sequence to the unknown end of the cDNA. The sequence in between is amplified by PCR with an anchor primer and a gene-specific...
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Cross-Sectional Research01:50

Cross-Sectional Research

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In cross-sectional research, a researcher compares multiple segments of the population at the same time. If they were interested in people's dietary habits, the researcher might directly compare different groups of people by age. Instead of following a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old...
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Data Collection III01:05

Data Collection III

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The physical assessment examines the patient for objective data that defines the patient's condition, and aids in formulating the nursing care plan. The purpose of physical assessment is a health status appraisal, which includes identifying health problems, and establishing a database for nursing intervention.
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Data Collection by Experiments01:13

Data Collection by Experiments

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Data collection is a systematic method of obtaining, observing, measuring, and analyzing accurate information. An experimental study is a standard method of data collection that involves the manipulation of the samples by applying some form of treatment prior to data collection. It refers to manipulating one variable to determine its changes on another variable. The sample subjected to treatment is known as “experimental units.”
An example of the experimental method is a public...
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The Road to a Research Database: A Team Approach, Limitless, and Never Ending.

Jana Tancredi1, Patricia Ferranda1, Sejal Patel1

  • 1Division of Cardiovascular Research, Hackensack University Medical Center, Hackensack Meridian Health, Hackensack, New Jersey, USA.

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A new Cardiovascular Research Database was developed to improve clinical practice and data collection for Cardiogenic Shock (CGS) patients. This resource enhances research reliability and identifies all CGS cases for better patient care.

Keywords:
cardiovascular databasecardiovascular diseasehealth care economicsintegrated datalifestyle

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Area of Science:

  • Cardiovascular Research
  • Health Informatics
  • Clinical Data Management

Background:

  • Development of a multidisciplinary Cardiovascular Research Database at Hackensack University Medical Center.
  • Initial focus on a Cardiogenic Shock (CGS) protocol and team creation.
  • Need for a comprehensive database to identify all CGS patients.

Observation:

  • Data from a subset of CGS patients indicated areas for improvement in clinical practice.
  • Gaps identified in current data collection methods for CGS patients.
  • Limitations in identifying the full scope of CGS patient population.

Findings:

  • Successful development and implementation of a comprehensive Cardiovascular Research Database.
  • Database facilitates reliable data extraction from Electronic Medical Records (EMR).
  • Data validation and refinement processes established based on project objectives.

Implications:

  • Enhanced data resource for clinicians to support cardiovascular research.
  • Potential to improve clinical practice and patient outcomes for CGS.
  • Foundation for future research and data-driven improvements in cardiovascular care.